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A Study on the Modeling of Obesity

  • Sung Young LimEmail author
  • Leticia Mucci da Conceição
  • Sergio G. Camorlinga
Chapter

Abstract

According to the World Health Organization (WHO), the number of obese people has almost tripled since 1975. In 2016 more than 1.9 billion adults 18 years and older were overweight. Of these over 650 million were obese. Overall, 39% of adults were overweight in 2016 and 13% were obese. If these circumstances persist, the financial burden of supporting obese people will place substantial pressures on healthcare expenditures. This is because several diseases such as cardiovascular diseases, diabetes, osteoarthritis, and others are profoundly affected by obesity. To solve this problem, it is very important to find out what are the causes of obesity. Contrary to most of the previous studies that are focused on one risk factor for obesity, we researched a variety of factors affecting obesity and their interdependencies by employing statistical analysis from a complex adaptive system perspective. Our goal is to use the research outcomes of this analysis to build a computer model for obesity. This model can potentially assist to save some associated costs from obesity by helping to prevent obesity and improve its management.

Notes

Acknowledgements

This work was supported in part by the University of Winnipeg Applied Computer Science Department, Mitacs Globalink program, and a Natural Sciences and Engineering Research Council of Canada Discovery Development Grant.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Sung Young Lim
    • 1
    Email author
  • Leticia Mucci da Conceição
    • 2
  • Sergio G. Camorlinga
    • 1
  1. 1.Department of Applied Computer ScienceThe University of WinnipegWinnipegCanada
  2. 2.Department of NutritionUniversity of São PauloSão José dos CamposBrazil

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